Collaborating Research Scientist

Join Heartflow’s world-class Research team as a Collaborating Research Scientist with a joint visiting researcher appointment in Professor Ben Glocker’s lab at Imperial College London. This position focuses on advancing state-of-the-art Generative AI technologies for Coronary Computed Tomography Angiography (CCTA). In this role, you will work on cutting edge academic research, IP generation and high-impact publications while ensuring that technical breakthroughs can be translated into Heartflow’s product-grade models.

At Imperial College: You will be an active member of one of the world’s leading medical imaging labs, participating in seminars, collaborating with academics, and engaging in the vibrant Imperial ecosystem in South Kensington.

At Heartflow: You will be a key stakeholder in our research roadmap, with access to massive, proprietary datasets that are unavailable to pure academic labs, with the opportunity for translation of your work into medical devices with global impact.

Key Responsibilities:

• Design and implement state-of-the-art generative architectures to synthesize high-fidelity, anatomically accurate CCTA image data.
• Publish and present at top-tier venues (such as MICCAI, ICCV, CVPR, NeurIPS).
• Provide technical reports and reproducible code to enable the translation of research into products by Research team members and development teams.
• Identify and protect new IP for Heartflow in emerging AI domains.
• Educate people across groups and departments on generative AI.

• Proven expertise in generative AI methods for computer vision or medical image analysis (diffusion models, flow matching, GANs, VAEs).
• Ability to clearly communicate complex ideas, tailoring content for diverse audiences.
• Experience developing generative AI systems with large-scale imaging datasets.
• Advanced proficiency in Python and PyTorch, with a commitment to writing clean, reproducible and scalable research code.
• A track record of first-author publications in top tier AI or medical imaging conferences. 

• Experience in causal modeling, and/or conditional generative models.
• Experience in developing multimodal generative AI systems.
• Experience developing AI systems with sparse and/or noisy labels.
• Experience building deep learning models for 3D medical image data.

• A PhD degree in computer science, engineering, math or similar technical field. 
• Preferably 2+ years related experience, in industry or academia, with Generative AI in computer vision or medical image analysis. 

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